Integrated Optimization of Thermal Processes In Heavy Oil Recovery - Annual report VISTA 2009

Annual report VISTA 2009

Integrated Optimization of Thermal Processes in Heavy Oil Recovery

Project director: Whitson, Curtis H., NTNU-IPT

Post-doc/ scholar: Ghasemi, Mohammad

Project duration: May 1, 2009 - May 1, 2012

Technical contact person in Statoil: Høier, Lars

Division head: Høier, Lars

Project number: 6346

Objective

The main objective of the project can be divided in two parts: (1) modelling the thermodynamic behaviour of solvent with heavy oils; and (2) optimization of thermal methods in heavy oil recovery. Modelling of phase behaviour of thermal process in heavy oil requires detailed information of heavy-end fractions. However, significant amount of heavy oil can not be distilled and remains as an undistillable solid. Adequate characterization of heavy oil is one of the main objectives in this work. Also, treatment of temperature-dependent component properties affecting viscosity. We aim to design new PVT experiments for heavy oil for a relevant range of pressure and temperature, as conventional procedures do not give data which are useful for thermal processes applied in heavy oil recovery.

Optimization of thermal methods into heavy oil is the second part of the research. The main goal is to build an integrated model that can connect reservoir to surface facility and use this model to optimize some thermal methods, in particular processes involving hydrocarbon solvents. The main objective of this part is to find the main variables that control the performance of those processes, and compare overall economics with more-standard methods such as SAGD.

Status (May 1 - Dec. 31, 2009)

Research: Extensive work on characterization of saturate, aromatic, resin and asphaltene (SARA) analyses has been made. Such analyses form the main characteristic of bitumen and heavy oil characterization.

We came up with a new methodology of gamma modelling SARA fractions through the analysis of data given by gel permeation chromatography (GPC) instrument. We chose to gamma fit each SARA analysis separately - i.e. a separate gamma model for saturates, aromatics, resins, and asphaltenes.

Another advantage of the new gamma-fitting method is that it requires only some points from the distribution trend to determine gamma parameters. This deviates from traditional gamma fitting which uses amounts and molecular weights of continuous and contiguous fractions, where total amount sums to unity. Molecular weight distributions are also much larger in SARA analyses than traditional crude oils, with a range in molecular weights from <100 to >10 000. The method developed has been tested using synthetic data, and reported SARA data for heavy oils.

Courses: 2 PhD course (corresponding to 15 credits) have been completed (grades A and B).

Teaching Assistantship: I assisted in the graduate course on unconventional IOR methods (Prof. Ole Torsaeter), spending considerable time teaching students how to use the CMG Stars simulator to model thermal heavy oil recovery. This knowledge will be used in our research as the SAGD method is the basis for comparison with the alternative solvent-based methods being investigated.